A Skewed General Variable Neighborhood Search Approach for Solving the Battery Swap Station Location-Routing Problem with Capacitated Electric Vehicles

Abstract

The station location problem plays an important role for reducing the amount of energy consumption in several logistics companies while identifying the location of the stations and the number of the located stations. In addition, an electric vehicle represents a significant factor to minimize the costs and to reduce the pollution caused by transport operations. To achieve these goals, we consider a new variant of location-routing problem for an electric vehicle with a single depot, such as the location decision is undertaken about the battery swap stations with an elaboration of vehicle routing. Our solution method is based on a skewed version of the variable neighborhood search (SVNS) metaheuristic. The local search corresponds to the mixed variable neighborhood descent (Mixed-VND) where a set of four routing neighborhood structures are described in the sequential VND procedure and nested with relocated station move. The solution generated by the local search is compared to the current solution according to a particular distance function. The obtained results for all available instances of the problem show the performance of our approach compared to those existing in the literature.